Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6418125 | Journal of Mathematical Analysis and Applications | 2015 | 31 Pages |
Abstract
In a general Hilbert framework, we consider continuous gradient-like dynamical systems for constrained multiobjective optimization involving nonsmooth convex objective functions. Based on the Yosida regularization of the subdifferential operators involved in the system, we obtain the existence of strong global trajectories. We prove a descent property for each objective function, and the convergence of trajectories to weak Pareto minima. This approach provides a dynamical endogenous weighting of the objective functions, a key property for applications in cooperative games, inverse problems, and numerical multiobjective optimization.
Related Topics
Physical Sciences and Engineering
Mathematics
Analysis
Authors
Hédy Attouch, Guillaume Garrigos, Xavier Goudou,